An interview with Nicolai Ommer: the RoboCupSoccer Small Measurement League

Kick-off in a Small Measurement League match. Picture credit score: Nicolai Ommer.

RoboCup is a world scientific initiative with the objective of advancing the cutting-edge of clever robots, AI and automation. The annual RoboCup occasion is because of happen from 15-21 July in Salvador, Brazil. The Soccer element of RoboCup includes a lot of Leagues, with certainly one of these being the Small Measurement League (SSL). We caught up with Govt Committee member Nicolai Ommer to search out out extra in regards to the SSL, how the auto referees work, and the way groups use AI.

May begin by giving us a fast introduction to the Small Measurement League?

Within the Small Measurement League (SSL) now we have 11 robots per crew – the one bodily RoboCup soccer league to have the complete variety of gamers. The robots are small, cylindrical robots on wheels and so they can transfer in any route. They’re self-built by the groups, so groups should do each the {hardware} and the programming, and a whole lot of issues should work collectively to make a crew work. The AI is central. We don’t have brokers, so groups have a central pc on the subject the place they’ll do all of the computation after which they ship the instructions to the robots in numerous abstractions. Some groups will simply ship velocity instructions, different groups ship a goal.

We’ve got a central imaginative and prescient system – that is maintained by the League, and has been since 2010. There are cameras above the sector to trace all of the robots and the ball, so everybody is aware of the place the robots are.

The robots can transfer as much as 4 meters per second (m/s), after this level it will get fairly unstable for the robots. They will change route in a short time, and the ball could be kicked at 6.5 m/s. It’s fairly quick and we’ve already needed to restrict the kick velocity. Beforehand we had a restrict of 8 m/s and earlier than that 10m/s. Nonetheless, no robotic can catch a ball with this velocity, so we determined to cut back it and put extra give attention to passing. This offers the keeper and the defenders an opportunity to truly intercept a kick.

It’s so quick that for people it’s fairly obscure all of the issues which are occurring. And that’s why, some years in the past, we launched auto refs, which assist so much in monitoring, particularly issues like collisions and so forth, the place the human referee can’t watch all the things on the similar time.

How do the auto refs work then, and is there a couple of working on the similar time?

Once we developed the present system, to maintain issues honest, we determined to have a number of implementations of an auto ref system. These impartial programs implement the identical guidelines after which we do a majority vote on the choices.

To do that we would have liked a center element, so some years in the past I began this undertaking to have a brand new sport controller. That is the person interface (UI) for the human referee who sits at a pc. Within the UI you see the present sport state, you possibly can manipulate the sport state, and this element coordinates the auto refs. The auto refs can join and report fouls. If just one auto ref detects the foul, it gained’t rely it. However, if each auto refs report the foul throughout the time window, then it’s counted. A part of the problem was to make this all visible for the operator to grasp. The human referee has the final phrase and makes the ultimate resolution.

We managed to determine two implementations. The goal was to have three implementations, which makes it simpler to type a majority. Nonetheless, it nonetheless works with simply two implementations and we’ve had this for a number of years now. The implementations are from two completely different groups who’re nonetheless lively.

How do the auto refs take care of collisions?

We are able to detect collisions from the information. Nonetheless, even for human referees it’s fairly onerous to find out who was at fault when two robots collide. So we needed to simply outline a rule, and all of the implementations of the auto ref implement the identical rule. We wrote within the rulebook actually particularly the way you calculate if a collision occurred and who was at fault. The primary consideration relies on the rate – under 1.5m/s it’s not a collision, above 1.5m/s it’s. There’s additionally one other issue, regarding the angle calculation, that we additionally consider to find out which robotic was at fault.

What else do the auto refs detect?

Different fouls embody the kick velocity, after which there’s fouls regarding the adherence to regular sport process. For instance, when the opposite crew has a free kick, then the opposing robots ought to keep a sure distance from the ball.

The auto refs additionally observe non-fouls, in different phrases sport occasions. For instance, when the ball leaves the sector. That’s the most typical occasion. This one is definitely not really easy to detect, notably if there’s a chip kick (the place the ball leaves the enjoying floor). With the digicam lens, the parabola of the ball could make it seem like it’s outdoors the sector of play when it isn’t. You want a strong filter to take care of this.

Additionally, when the auto refs detect a objective, we don’t belief them fully. When a objective is detected, we name it a “doable objective”. The match is halted instantly, all of the robots cease, and the human referee can verify all of the out there knowledge earlier than awarding the objective.

You’ve been concerned within the League for a lot of years. How has the League and the efficiency of the robots advanced over that point?

My first RoboCup was in 2012. The introduction of the auto refs has made the play much more fluent. Earlier than this, we additionally launched the idea of ball placement, so the robots would place the ball themselves for a free kick, or kick off, for instance.

From the {hardware} aspect, the primary enchancment lately has been dribbling the ball in one-on-one conditions. There has additionally been an enchancment within the specialised expertise carried out by robots with a ball. For instance, some years in the past, one crew (ZJUNlict) developed robots that might pull the ball backwards with them, transfer round defenders after which shoot on the objective. This was an surprising motion, which we hadn’t seen earlier than. Earlier than this you needed to do a move to trick the defenders. Our crew, TIGERs Mannheim, has additionally improved on this space now. But it surely’s actually troublesome to do that and requires a whole lot of tuning. It actually will depend on the sector, the carpet, which isn’t standardized. So there’s a bit of little bit of luck that your particularly constructed {hardware} is definitely performing properly on the competitors carpet.

The Small Measurement League Grand Ultimate at RoboCup 2024 in Eindhoven, Netherlands. TIGERs Mannheim vs. ZJUNlict. Video credit score: TIGERs Mannheim. You will discover the TIGERs’ YouTube channel right here.

What are a few of the challenges within the League?

One huge problem, and in addition perhaps it’s a great factor for the League, is that now we have a whole lot of undergraduate college students within the groups. These college students have a tendency to depart the groups after their Bachelor’s or Grasp’s diploma, the crew members all change fairly frequently, and that implies that it’s troublesome to retain information within the groups. It’s a problem to maintain the efficiency of the crew; it’s even onerous to breed what earlier members achieved. That’s why we don’t have giant steps ahead, as a result of groups should repeat the identical issues when new members be a part of. Nonetheless, it’s good for the scholars as a result of they actually be taught so much from the expertise.

We’re constantly engaged on figuring out issues which we will make out there for everybody. In 2010 the imaginative and prescient system was established. It was an enormous issue, which means that groups didn’t should do pc imaginative and prescient. And we’re presently taking a look at establishing requirements for wi-fi communication – that is presently finished by everybody on their very own. We need to advance the League, however on the similar time, we additionally need to have this nature of with the ability to be taught, with the ability to do all of the issues themselves in the event that they need to.

You really want to have a crew of individuals from completely different areas – mechanical engineering, electronics, undertaking administration. You additionally should get sponsors, and it’s a must to promote your undertaking, get college students in your crew.

May you speak about a few of the AI parts to the League?

Most of our software program is script-based, however we apply machine studying for small, delicate issues.

In my crew, for instance, we do mannequin calibration with fairly easy algorithms. We’ve got a particular mannequin for the chip kick, and one other for the robotic. The wheel friction is sort of sophisticated, so we provide you with a mannequin after which we gather the information and use machine studying to detect the parameters.

For the precise match technique, one good instance is from the crew CMDragons. One yr you may actually observe that that they had skilled their mannequin in order that, as soon as they scored objective, they upvoted the technique that they utilized earlier than that. You may actually see that the opponent reacted the identical means on a regular basis. They had been in a position to rating a number of targets, utilizing the identical technique many times, as a result of they discovered that if one technique labored, they may use it once more.

For our crew, the TIGERs, our software program could be very a lot based mostly on calculating scores for a way good a move is, how properly can a move be intercepted, and the way we will enhance the scenario with a selected move. That is hard-coded typically, with some geometry-based calculations, however there’s additionally some fine-tuning. If we rating a objective then we monitor again and see the place the move got here from and we give bonuses on a few of the rating calculations. It’s extra sophisticated than this, after all, however basically it’s what we attempt to do by studying in the course of the sport.

Individuals typically ask why we don’t do extra with AI, and I believe the primary problem is that, in comparison with different use circumstances, we don’t have that a lot knowledge. It’s onerous to get the information. In our case now we have actual {hardware} and we can not simply do matches all day lengthy for days on finish – the robots would break, and so they must be supervised. Throughout a contest, we solely have about 5 to seven matches in complete. In 2016, we began to file all of the video games with a machine-readable format. All of the positions are encoded, together with the referee choices, and all the things is in a log file which we publish centrally. I hope that with this rising quantity of knowledge we will truly apply some machine studying algorithms to see what earlier matches and former methods did, and perhaps get some insights.

What plans do you might have in your crew, the TIGERs?

We’ve got truly gained the competitors for the final 4 years. We hope that there shall be another groups who can problem us. Our defence has probably not been challenged so now we have a tough time discovering weaknesses. We truly play in opposition to ourselves in simulation.

One factor that we need to enhance on is precision as a result of there’s nonetheless some guide work to get all the things calibrated and dealing as exactly as we would like it. If some small element isn’t working, for instance the dribbling, then it dangers the entire event. So we’re engaged on making all these calibration processes simpler, and to do extra automated knowledge processing to find out the very best parameters. Lately we’ve labored so much on dribbling within the 1 vs 1 conditions. This has been a very huge enchancment for us and we’re nonetheless engaged on that.

About Nicolai

Nicolai Ommer is a Software program Engineer and Architect at QAware in Munich, specializing in designing and constructing strong software program programs. He holds a B.Sc. in Utilized Pc Science and an M.Sc. in Autonomous Methods. Nicolai started his journey in robotics with Crew TIGERs Mannheim, taking part in his first RoboCup in 2012. His dedication led him to hitch the RoboCup Small Measurement League Technical Committee and, in 2023, the Govt Committee. Keen about innovation and collaboration, Nicolai combines tutorial perception with sensible expertise to push the boundaries of clever programs and contribute to the worldwide robotics and software program engineering communities.